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L-shaped association of triglyceride glucose-body mass index and self-rated mental health among the middle-aged and older adults

A national cohort study in China

Bibliographic Data

ID22074347
AuthorsYanqin Li (0000-0003-0701-7326, Nanfang Hospital), Qi Gao (0000-0002-0461-6254, Wuhan Puai Hospital), Fan Luo (0000-0001-9812-2476, Nanfang Hospital), Yuxin Lin (0000-0003-1758-6215, Nanfang Hospital), Ruqi Xu (Guangdong Medical College), Pingping Li (0000-0003-4997-4239, Nanfang Hospital), Yuping Zhang (0000-0003-1055-2071, Nanfang Hospital), Jiao Liu (0000-0002-9371-0778, Nanfang Hospital), Hongrui Zhan (0000-0003-4207-2574, Sun Yat-sen University, corresponding author), Licong Su (0000-0002-3085-909X, Nanfang Hospital, corresponding author)
Year2025
Volume13
Pages1672881-1672881
Publication date2025-11-25
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueFrontiers in Public Health (JOURNAL)
Journal identifiersISSN: 2296-2565 • E-ISSN: 2296-2565
PublisherFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2025.1672881
PMID41377716
OpenAlexW4416605928
LanguageEN
References cited54

Background Previous studies have shown that the triglyceride glucose-body mass index (TyG-BMI) is associated with cardiovascular disease, stroke, and cognition. Its relationship with mental health remains underexplored. We aimed to investigate the association between TyG-BMI and mental health in Chinese adults. Methods This study utilized data from the China Health and Nutrition Survey (CHNS), an ongoing longitudinal cohort. Participants aged ≥45 years who completed at least two survey rounds between 2009 and 2015 were included. The TyG index was calculated as ln [triglycerides (mg/dL) × fasting blood glucose (mg/dL) / 2]. BMI was calculated as weight (kg) divided by height squared (m 2 ). The TyG-BMI was the product of the TyG index and BMI. Self-rated mental health was assessed using a composite score based on three CHNS questions regarding vitality, happiness, and optimism. Restricted cubic spline (RCS) curves and two-piecewise multivariable Cox hazard regression models, which were adjusted for sociodemographic, lifestyle, and cardiometabolic factors, were employed to explore the relationship between the TyG-BMI and self-rated mental health. Models were adjusted for sociodemographic, lifestyle, and cardiometabolic factors. Results Among 2,951 participants (47.6% male, median age 56.0 [25th, 75th percentile: 51, 64] years), the median TyG-BMI was 204.3 [25th, 75th percentile: 179.6, 231.8]. Over a median follow-up of 6.0 [2.0, 6.1] years, 1,026 (34.8%) incident was identified poor self-rated mental health. RCS curves indicated an L-shaped association between TyG-BMI and self-rated mental health ( p for non-linear = 0.033), with an inflection point of 204.3. Below this threshold, each 10-unit increase in TyG-BMI was associated with a 6% decrease in self-rated mental health risk (adjusted hazard ratio [aHR] = 0.94, 95% confidence interval [CI]: 0.90–0.99). Each 1-standard deviation (SD) increase corresponded to a 20% risk reduction (aHR = 0.80, 95% CI: 0.67–0.96). Above the threshold, no significant association was observed. Subgroup and sensitivity analyses yielded consistent results. Conclusion This study revealed an L-shaped association between TyG-BMI and self-rated mental health in mentally healthy, middle-aged and older Chinese individuals. Our findings suggest that TyG-BMI may serve as an effective tool for enhancing the primary prevention of mental health

Body mass index · China · Cohort · Cohort study · Mental health · Bariatric Surgery and Outcomes · Dementia and Cognitive Impairment Research · Diabetes, Cardiovascular Risks, and Lipoproteins

  • Comparison of Random Forest and Parametric Imputation Models for Imputing Missing Data Using Mice

    Open Access•Anoop D Shah, Jonathan Bartlett et al.•American Journal of Epidemiology•2014

  • The C hina H ealth and N utrition S urvey, 1989–2011

    Open Access•Bing Zhang, F Y Zhai et al.•Obesity Reviews•2014

  • Depression

    Open Access•Gin S Malhi, J John Mann•The Lancet•2018

  • Overweight, Obesity, and Depression

    Floriana S Luppino, Leonore de Wit et al.•Archives of General Psychiatry•2010

  • Prevalence, treatment, and associated disability of mental disorders in four provinces in China during 2001–05

    Open Access•Michael R Phillips, Jingxuan Zhang et al.•The Lancet•2009

  • Cohort Profile

    Barry M Popkin, Shuming Du et al.•International Journal of…•2010

  • Diagnosis and Classification of Diabetes Mellitus

    American Diabetes Association•Diabetes Care•2014

  • Multicollinearity and misleading statistical results

    Open Access•Jonghae Kim•Korean Journal of Anesthesiology•2019

  • A New Equation to Estimate Glomerular Filtration Rate

    Open Access•Andrew S Levey, Lesley A Stevens et al.•Annals of Internal Medicine•2009

  • The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement

    Open Access•Erik Von Elm, David G Altman et al.•The Lancet•2007

  • Predicting depressive symptom by cardiometabolic indicators in mid-aged and older adults in China

    Open Access•Ying Wang, Xiaoyun Zhang et al.•Frontiers in Psychiatry•2023

  • The Associations between Meeting 24-Hour Movement Guidelines (24-HMG) and Self-Rated Physical and Mental Health in Older Adults—Cross Sectional Evidence from China

    Open Access•Lin Luo, Yunxia Cao et al.•International Journal of…•2022

  • Mental health in children and adolescents with overweight or obesity

    Open Access•Lucas-Johann Förster, Mandy Vogel et al.•BMC Public Health•2023

  • Depression and body mass index, a u-shaped association

    Open Access•Leonore de Wit, Leonore M de Wit et al.•BMC Public Health•2009

  • Body mass index and subjective well-being in young adults

    Open Access•Milla S Linna, Jaakko Kaprio et al.•BMC Public Health•2013

  • The association between body mass index and health-related quality of life

    Open Access•Wilma M Hopman, Claudie Berger et al.•Quality of Life Research•2007

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